6256 Open source projects that are alternatives of or similar to Neural Networks

Image augmentation library in Python for machine learning.

Place recognition with WiFi fingerprints using Autoencoders and Neural Networks

This is just a collection of projects that made during my DEEPLEARNING NANODEGREE by UDACITY

pytorch 包教不包会

Keras tutorial for beginners (using TF backend)

Contains my explorations of TensorFlow 2.x

머신러닝 입문자 혹은 스터디를 준비하시는 분들에게 도움이 되고자 만든 repository입니다. (This repository is intented for helping whom are interested in machine learning study)

Aspect-Based Sentiment Analysis

Applying Data Science and Machine Learning to Solve Real World Business Problems

Visualisations for Convolutional Neural Networks in Pytorch

Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?

These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.

Plain python implementations of basic machine learning algorithms

PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"

由淺入深的深度學習資源 Collection of deep learning materials for everyone

Grokking Deep Reinforcement Learning

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow

🎨 Artistic neural style transfer with tweaks (pytorch).

An introductory series to Reinforcement Learning (RL) with comprehensive step-by-step tutorials.

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

Adventure into using multi attention recurrent neural networks for time-series (city traffic) for the 2017-11-18 McKinsey IronMan (24h non-stop) prediction challenge

Machine Learning notebooks for refreshing concepts.

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

Codes for weekly challenges on Deep Learning by Siraj

links to conference publications in graph-based deep learning

Machine Learning Practical course repository

AI-related tutorials. Access any of them for free → https://towardsai.net/editorial

AI for everyone! 🎉 Neural networks, tools and a library we use in Supervisely

Probabilistic reasoning and statistical analysis in TensorFlow

Amazon Forest Computer Vision: Satellite Image tagging code using PyTorch / Keras with lots of PyTorch tricks

Complete Assignments for CS231n: Convolutional Neural Networks for Visual Recognition

A simple probabilistic programming language.

Repo for the Deep Reinforcement Learning Nanodegree program

This repository contains my full work and notes on Coursera's NLP Specialization (Natural Language Processing) taught by the instructor Younes Bensouda Mourri and Łukasz Kaiser offered by deeplearning.ai

A clear, concise, simple yet powerful and efficient API for deep learning.

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.

Computations and statistics on manifolds with geometric structures.

Support content for my blog

Deep Learning Specialization by Andrew Ng on Coursera.

Daily Dose of Neural Network that Everyone Needs

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

Udacity Self-Driving Car Engineer Nanodegree. Project: Build a Traffic Sign Recognition Classifier

A collection of Bayesian data analysis recipes using PyMC3

This toolbox is support material for the book on CNN (http://www.convolution.network).

Official Repsoitory for "Mish: A Self Regularized Non-Monotonic Neural Activation Function" [BMVC 2020]

This repository stores the files used for my summer internship's work on "teacher-student learning", an experimental method for training deep neural networks using a trained teacher model.

RadIO is a library for data science research of computed tomography imaging

Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

Lab Materials for MIT 6.S191: Introduction to Deep Learning

Code for the Lovász-Softmax loss (CVPR 2018)

Books, papers and links to latest research in ML/AI